Impact of optic media opacities and image compression on quantitative analysis of optical coherence tomography

To analyze the impact of opacities in the optical pathway and image compression of 32-bit raw data to 8-bit jpg images on quantified optical coherence tomography (OCT) image analysis.

[The image of the dentist. Part 1: Results of a literature search]

The dentist enjoys a high degree of professional independence. He is seen as reliable and productive at work while carrying a big responsibility. His foremost social responsibility is to treat patients suffering from toothache and to promote oral health prevention for all people, regardless of their social status. At the same time, the dentist is prestigious, respected and honest. Comparable to other professions, however, dentistry is under public pressure. Media often associate the dental profession with negative properties such as sadism, immorality, or madness. Does the image of the dental profession suffer in this context? Our first article discusses the environmental factors which are identifiable to influence both each dentist and ultimately the whole image of dentistry.

Effects of non-ionic iodinated contrast media on patient heart rate and pressures during intra-cardiac or intra-arterial injection

PURPOSE: To compare the effects on heart rate (HR), on left ventricular (LV) or arterial pressures, and the general safety of a non-ionic low-osmolar contrast medium (CM) and a non-ionic iso-osmolar CM in patients undergoing cardiac angiography (CA) or peripheral intra-arterial digital subtraction angiography (IA-DSA). MATERIALS AND METHODS: Two double-blind, randomized studies were conducted in 216 patients who underwent CA (n=120) or peripheral IA-DSA (n=96). Patients referred for CA received a low-osmolar monomeric CM (iomeprol-350, n=60) or an iso-osmolar dimeric CM (iodixanol-320; n=60). HR and LV peak systolic and end-diastolic pressures were determined before and after the first injection during left and right coronary arteriography and left ventriculography. Monitoring for all types of adverse event (AE) was performed for 24 h following the procedure. t-tests were performed to compare CM for effects on HR. Patients referred for IA-DSA received iomeprol-300 (n=49) or iodixanol-320 (n=47). HR and arterial blood pressure (BP) were evaluated before and after the first 4 injections. Monitoring for AE was performed for 4 h following the procedure. Repeated-measures ANOVA was used to compare mean HR changes across the first 4 injections, whereas changes after the first injection were compared using t-tests. RESULTS: No significant differences were noted between iomeprol and iodixanol in terms of mean changes in HR during left coronary arteriography (p=0.8), right coronary arteriography (p=0.9), and left ventriculography (p=0.8). In patients undergoing IA-DSA, no differences between CM were noted for effects on mean HR after the first injection (p=0.6) or across the first 4 injections (p=0.2). No significant differences (p>0.05) were noted in terms of effects on arterial BP in either study or on LV pressures in patients undergoing CA. Non-serious AE considered possibly CM-related (primarily headache and events affecting the cardiovascular and digestive systems) were reported more frequently by patients undergoing CA and more frequently after iodixanol (14/60 [23.3%] and 2/47 [4.3%]; CA and IA-DSA, respectively) than iomeprol (10/60 [16.7%] and 1/49 [2%], respectively). CONCLUSIONS: Iomeprol and iodixanol are safe and have equally negligible effects on HR and LV pressures or arterial BP during and after selective intra-cardiac injection and peripheral IA-DSA. CLINICAL APPLICATION: Iomeprol and iodixanol are safe and equally well tolerated with regard to cardiac rhythm and clinical preference should be based on diagnostic image quality alone.

Effect of X-ray tube parameters, iodine concentration, and patient size on image quality in pulmonary computed tomography angiography: a chest-phantom-study

OBJECTIVES: The aim of this phantom study was to evaluate the contrast-to-noise ratio (CNR) in pulmonary computed tomography (CT)-angiography for 300 and 400 mg iodine/mL contrast media using variable x-ray tube parameters and patient sizes. We also analyzed the possible strategies of dose reduction in patients with different sizes. MATERIALS AND METHODS: The segmental pulmonary arteries were simulated by plastic tubes filled with 1:30 diluted solutions of 300 and 400 mg iodine/mL contrast media in a chest phantom mimicking thick, intermediate, and thin patients. Volume scanning was done with a CT scanner at 80, 100, 120, and 140 kVp. Tube current-time products (mAs) varied between 50 and 120% of the optimal value given by the built-in automatic dose optimization protocol. Attenuation values and CNR for both contrast media were evaluated and compared with the volume CT dose index (CTDI(vol)). Figure of merit, calculated as CNR/CTDIvol, was used to quantify image quality improvement per exposure risk to the patient. RESULTS: Attenuation of iodinated contrast media increased both with decreasing tube voltage and patient size. A CTDIvol reduction by 44% was achieved in the thin phantom with the use of 80 instead of 140 kVp without deterioration of CNR. Figure of merit correlated with kVp in the thin phantom (r = -0.897 to -0.999; P < 0.05) but not in the intermediate and thick phantoms (P = 0.09-0.71), reflecting a decreasing benefit of tube voltage reduction on image quality as the thickness of the phantom increased. Compared with the 300 mg iodine/mL concentration, the same CNR for 400 mg iodine/mL contrast medium was achieved at a lower CTDIvol by 18 to 40%, depending on phantom size and applied tube voltage. CONCLUSIONS: Low kVp protocols for pulmonary embolism are potentially advantageous especially in thin and, to a lesser extent, in intermediate patients. Thin patients profit from low voltage protocols preserving a good CNR at a lower exposure. The use of 80 kVp in obese patients may be problematic because of the limitation of the tube current available, reduced CNR, and high skin dose. The high CNR of the 400 mg iodine/mL contrast medium together with lower tube energy and/or current can be used for exposure reduction.

Image Space Adaptive Rendering

In this thesis, we develop an adaptive framework for Monte Carlo rendering, and more specifically for Monte Carlo Path Tracing (MCPT) and its derivatives. MCPT is attractive because it can handle a wide variety of light transport effects, such as depth of field, motion blur, indirect illumination, participating media, and others, in an elegant and unified framework. However, MCPT is a sampling-based approach, and is only guaranteed to converge in the limit, as the sampling rate grows to infinity. At finite sampling rates, MCPT renderings are often plagued by noise artifacts that can be visually distracting. The adaptive framework developed in this thesis leverages two core strategies to address noise artifacts in renderings: adaptive sampling and adaptive reconstruction. Adaptive sampling consists in increasing the sampling rate on a per pixel basis, to ensure that each pixel value is below a predefined error threshold. Adaptive reconstruction leverages the available samples on a per pixel basis, in an attempt to have an optimal trade-off between minimizing the residual noise artifacts and preserving the edges in the image. In our framework, we greedily minimize the relative Mean Squared Error (rMSE) of the rendering by iterating over sampling and reconstruction steps. Given an initial set of samples, the reconstruction step aims at producing the rendering with the lowest rMSE on a per pixel basis, and the next sampling step then further reduces the rMSE by distributing additional samples according to the magnitude of the residual rMSE of the reconstruction. This iterative approach tightly couples the adaptive sampling and adaptive reconstruction strategies, by ensuring that we only sample densely regions of the image where adaptive reconstruction cannot properly resolve the noise. In a first implementation of our framework, we demonstrate the usefulness of our greedy error minimization using a simple reconstruction scheme leveraging a filterbank of isotropic Gaussian filters. In a second implementation, we integrate a powerful edge aware filter that can adapt to the anisotropy of the image. Finally, in a third implementation, we leverage auxiliary feature buffers that encode scene information (such as surface normals, position, or texture), to improve the robustness of the reconstruction in the presence of strong noise.

Feasible Dose Reduction in Routine Chest Computed Tomography Maintaining Constant Image Quality Using the Last Three Scanner Generations: From Filtered Back Projection to Sinogram-affirmed Iterative Reconstruction and Impact of the Novel Fully Integrated Detector Design Minimizing Electronic Noise

OBJECTIVE The aim of the present study was to evaluate a dose reduction in contrast-enhanced chest computed tomography (CT) by comparing the three latest generations of Siemens CT scanners used in clinical practice. We analyzed the amount of radiation used with filtered back projection (FBP) and an iterative reconstruction (IR) algorithm to yield the same image quality. Furthermore, the influence on the radiation dose of the most recent integrated circuit detector (ICD; Stellar detector, Siemens Healthcare, Erlangen, Germany) was investigated. MATERIALS AND METHODS 136 Patients were included. Scan parameters were set to a thorax routine: SOMATOM Sensation 64 (FBP), SOMATOM Definition Flash (IR), and SOMATOM Definition Edge (ICD and IR). Tube current was set constantly to the reference level of 100 mA automated tube current modulation using reference milliamperes. Care kV was used on the Flash and Edge scanner, while tube potential was individually selected between 100 and 140 kVp by the medical technologists at the SOMATOM Sensation. Quality assessment was performed on soft-tissue kernel reconstruction. Dose was represented by the dose length product. RESULTS Dose-length product (DLP) with FBP for the average chest CT was 308 mGy*cm ± 99.6. In contrast, the DLP for the chest CT with IR algorithm was 196.8 mGy*cm ± 68.8 (P = 0.0001). Further decline in dose can be noted with IR and the ICD: DLP: 166.4 mGy*cm ± 54.5 (P = 0.033). The dose reduction compared to FBP was 36.1% with IR and 45.6% with IR/ICD. Signal-to-noise ratio (SNR) was favorable in the aorta, bone, and soft tissue for IR/ICD in combination compared to FBP (the P values ranged from 0.003 to 0.048). Overall contrast-to-noise ratio (CNR) improved with declining DLP. CONCLUSION The most recent technical developments, namely IR in combination with integrated circuit detectors, can significantly lower radiation dose in chest CT examinations.

Automatic X-ray landmark detection and shape segmentation via data-driven joint estimation of image displacements

In this paper, we propose a new method for fully-automatic landmark detection and shape segmentation in X-ray images. To detect landmarks, we estimate the displacements from some randomly sampled image patches to the (unknown) landmark positions, and then we integrate these predictions via a voting scheme. Our key contribution is a new algorithm for estimating these displacements. Different from other methods where each image patch independently predicts its displacement, we jointly estimate the displacements from all patches together in a data driven way, by considering not only the training data but also geometric constraints on the test image. The displacements estimation is formulated as a convex optimization problem that can be solved efficiently. Finally, we use the sparse shape composition model as the a priori information to regularize the landmark positions and thus generate the segmented shape contour. We validate our method on X-ray image datasets of three different anatomical structures: complete femur, proximal femur and pelvis. Experiments show that our method is accurate and robust in landmark detection, and, combined with the shape model, gives a better or comparable performance in shape segmentation compared to state-of-the art methods. Finally, a preliminary study using CT data shows the extensibility of our method to 3D data.